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Grey model GM (1,1) has been widely used in short-term prediction of energy production and consumption due to its advantages in data sets with small numbers of samples. However, the existing GM (1,1) modelling method can merely forecast the general trend of a time series but fails to identify and predicts the seasonal fluctuations. In the research, the authors propose a data grouping approach based...
In this study, we investigate the factors influencing the fluctuation in the export trade of China's new energy industry, and the export trade fluctuations in its subdivision industries, using a constant market share (CMS) model and UN Comtrade export data for China's new energy industry from 1996 to 2014. The study reveals that the import demands of the international market for China's new energy...
The Nash nonlinear grey Bernoulli model (NNGBM(1,1)) is a flexible grey system model that can be used to forecast nonlinear data. In order to better forecast the fluctuations contained in the original data, a Fourier Nash nonlinear grey Bernoulli model (FNNGBM(1,1)) is proposed in this research. The parameters optimization of FNNGBM(1,1) is formulated as a combinatorial optimization problem and is...
Real option value is determined by a variety of uncertain factors. It is very important to assess the intensity and importance of these factors affecting the real option value for investment decision makers. In this paper, the real option value system is viewed as a grey system and grey relational model (GRM) is employed to analyze the factors affecting the real option value. In order to eliminate...
Based on the basic assumption of stable relationship among different factors in the grey system theory and grey sequence entropy, it presents a new method for the first time how to determine the weight of incidence coefficient in grey incidence analysis. By defining the distributing density value of weighted grey incidence coefficient, this paper composes a grey sequence in order to establish an optimization...
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